There are substantial individual differences (resilience and vulnerability) in performance resulting from sleep loss and psychosocial stress, but predictive potential biomarkers remain elusive. Similarly, marked changes in the cardiovascular system from sleep loss and stress include an increased risk for cardiovascular disease. It remains unknown whether key hemodynamic markers, including left ventricular ejection time (LVET), stroke volume (SV), heart rate (HR), cardiac index (CI), blood pressure (BP), and systemic vascular resistance index (SVRI), differ in resilient vs. vulnerable individuals and predict differential performance resilience with sleep loss and stress. We investigated for the first time whether the combination of total sleep deprivation (TSD) and psychological stress affected a comprehensive set of hemodynamic measures in healthy adults, and whether these measures differentiated neurobehavioral performance in resilient and vulnerable individuals. Thirty-two healthy adults (ages 27–53; 14 females) participated in a 5-day experiment in the Human Exploration Research Analog (HERA), a high-fidelity National Aeronautics and Space Administration (NASA) space analog isolation facility, consisting of two baseline nights, 39 h TSD, and two recovery nights. A modified Trier Social Stress Test induced psychological stress during TSD. Cardiovascular measure collection [SV, HR, CI, LVET, BP, and SVRI] and neurobehavioral performance testing (including a behavioral attention task and a rating of subjective sleepiness) occurred at six and 11 timepoints, respectively. Individuals with longer pre-study LVET (determined by a median split on pre-study LVET) tended to have poorer performance during TSD and stress. Resilient and vulnerable groups (determined by a median split on average TSD performance) showed significantly different profiles of SV, HR, CI, and LVET. Importantly, LVET at pre-study, but not other hemodynamic measures, reliably differentiated neurobehavioral performance during TSD and stress, and therefore may be a biomarker. Future studies should investigate whether the non-invasive marker, LVET, determines risk for adverse health outcomes.

Autism spectrum disorders (ASD) represent a continuum of cognitive and social problems that vary considerably in both impact and presentation for each child affected. Although successful interventions have been developed that target specific skill deficits often exhibited by children with autism, many of those interventions are exclusively behavioral in nature, and do not address the cognitive components of presenting problems. The use of cognitive-behavioral therapy (CBT) to address issues related to ASD, however, has been increasing. More specifically, CBT interventions have often been used to address issues of anxiety for children with ASD, and these promising results may be useful to inform practices in schools. This review examines existing literature on CBT interventions that have been evaluated with children with ASD and suggests methods and implications for adapting these interventions for use within the school setting. C 2011 Wiley Periodicals, Inc.

Background‘Mitochondrial Myopathy’ (MM) refers to genetically‐confirmed Primary Mitochondrial Disease (PMD) that predominantly impairs skeletal muscle function. Validated outcome measures encompassing core MM domains of muscle weakness, muscle fatigue, imbalance, impaired dexterity, and exercise intolerance do not exist. The goal of this study was to validate clinically‐meaningful, quantitative outcome measures specific to MM.MethodsThis was a single centre study. Objective measures evaluated included hand‐held dynamometry, balance assessments, Nine Hole Peg Test (9HPT), Functional Dexterity Test (FDT), 30 second Sit to Stand (30s STS), and 6‐minute walk test (6MWT). Results were assessed as z‐scores, with < −2 standard deviations considered abnormal. Performance relative to the North Star Ambulatory Assessment (NSAA) of functional mobility was assessed by Pearson's correlation.ResultsIn genetically‐confirmed MM participants [n = 59, mean age 21.6 ± 13.9 (range 7 – 64.6 years), 44.1% male], with nuclear gene aetiologies, n = 18/59, or mitochondrial (mtDNA) aetiologies, n = 41/59, dynamometry measurements demonstrated both proximal [dominant elbow flexion (−2.6 ± 2.1, mean z‐score ± standard deviation, SD), hip flexion (−2.5 ± 2.3), and knee flexion (−2.8 ± 1.3)] and distal muscle weakness [wrist extension (−3.4 ± 1.7), palmar pinch (−2.5 ± 2.8), and ankle dorsiflexion (−2.4 ± 2.5)]. Balance [Tandem Stance (TS) Eyes Open (−3.2 ± 8.8, n = 53) and TS Eyes Closed (−2.6 ± 2.7, n = 52)] and dexterity [FDT (−5.9 ± 6.0, n = 44) and 9HPT (−8.3 ± 11.2, n = 53)] assessments also revealed impairment. Exercise intolerance was confirmed by strength‐based 30s STS test (−2.0 ± 0.8, n = 38) and mobility‐based 6MWT mean z‐score (−2.9 ± 1.3, n = 46) with significant decline in minute distances (slope −0.9, p = 0.03, n = 46). Muscle fatigue was quantified by dynamometry repetitions with strength decrement noted between first and sixth repetitions at dominant elbow flexors (−14.7 ± 2.2%, mean ± standard error, SEM, n = 21). All assessments were incorporated in the MM‐Composite Assessment Tool (MM‐COAST). MM‐COAST composite score for MM participants was 1.3 ± 0.1 (n = 53) with a higher score indicating greater MM disease severity, and correlated to NSAA (r = −0.64, p < 0.0001, n = 52) to indicate clinical meaning. Test–retest reliability of MM‐COAST assessments in an MM subset (n = 14) revealed an intraclass correlation coefficient (ICC) of 0.81 (95% confidence interval: 0.59–0.92) indicating good reliability.ConclusionsWe have developed and successfully validated a MM‐specific Composite Assessment Tool to quantify the key domains of MM, shown to be abnormal in a Definite MM cohort. MM‐COAST may hold particular utility as a meaningful outcome measure in future MM intervention trials.

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Cortisol and C-reactive protein (CRP) typically change during total sleep deprivation (TSD) and psychological stress; however, it remains unknown whether these biological markers can differentiate robust individual differences in neurobehavioral performance and self-rated sleepiness resulting from these stressors. Additionally, little is known about cortisol and CRP recovery after TSD. In our study, 32 healthy adults (ages 27–53; mean ± SD, 35.1 ± 7.1 years; 14 females) participated in a highly controlled 5-day experiment in the Human Exploration Research Analog (HERA), a high-fidelity National Aeronautics and Space Administration (NASA) space analog isolation facility, consisting of two baseline nights, 39 h TSD, and two recovery nights. Psychological stress was induced by a modified Trier Social Stress Test (TSST) on the afternoon of TSD. Salivary cortisol and plasma CRP were obtained at six time points, before (pre-study), during [baseline, the morning of TSD (TSD AM), the afternoon of TSD (TSD PM), and recovery], and after (post-study) the experiment. A neurobehavioral test battery, including measures of behavioral attention and cognitive throughput, and a self-report measure of sleepiness, was administered 11 times. Resilient and vulnerable groups were defined by a median split on the average TSD performance or sleepiness score. Low and high pre-study cortisol and CRP were defined by a median split on respective values at pre-study. Cortisol and CRP both changed significantly across the study, with cortisol, but not CRP, increasing during TSD. During recovery, cortisol levels did not return to pre-TSD levels, whereas CRP levels did not differ from baseline. When sex was added as a between-subject factor, the time × sex interaction was significant for cortisol. Resilient and vulnerable groups did not differ in cortisol and CRP, and low and high pre-study cortisol/CRP groups did not differ on performance tasks or self-reported sleepiness. Thus, both cortisol and CRP reliably changed in a normal, healthy population as a result of sleep loss; however, cortisol and CRP were not markers of neurobehavioral resilience to TSD and stress in this study.